The present invention relates in general to the field of resource management and, more particularly, an assessment method used to select a suitable candidate, typically from a large pool of candidates, for a particular position in an organization.
In various known, prevalent assessment methods, candidates are tested for general or pre-determined abilities. The candidate attaining the best test score is considered to be the best candidate. The test may be a written (pen and paper) test or a computerized test.
More sophisticated and expensive methods are performed by assessment centers, which in addition to the above test, conduct a personal interview and provide a professional opinion with respect to each candidate.
Conventional methods of resource planning further include manually searching a personnel base to match appropriately qualified candidates to the technical resource requirements of the organization. Such technical resource requirements can include, for example, a pool of personnel that have the technical skills needed to meet the needs of the organization. After candidates are matched to these needs, deficiencies in other skills may remain. Because conventional methods do not effectively compare the abilities and characteristics of the candidates to the customer's needs, the service provider may have personnel assigned to a customer who are lacking essential skills to perform the service required by the customer.
Moreover, these methods fail to consider, in any comprehensive and scientific manner, the different standards and requirements of particular organizations, differences that may significantly lower predictions of a ‘standard’ assessment.
U.S. Pat. No. 6,289,340 to Puram, et al., teaches the selection of a candidate from a pool of candidates to fill a position based on the skills held by the candidate, the skills desired for the position and the priority of the skills for the position. Pre-defined lists of skills are used to develop detailed profiles of the candidates and the positions to be filled for better matching. To compare and rank candidates, adjusted skills scores are used which are limited by the priority of the skill for the position, yielding best-fit matches.
Once a sub-pool of satisfactory size is identified, the next task is to determine which of the adequate candidates has skills and experience that most closely match what is needed or desired for a position. For each skill, the candidate's score is compared to the maximum score needed by the employer. If the candidate's score exceeds the maximum score requested for a skill, then the system generates an adjusted score for that candidate for that skill that equals the maximum scored needed by the employer. If the candidate's score does not exceed the maximum score for that skill, then the adjusted score for that skill equals the actual score. The adjusted score is stored; the candidate's actual score is not over-written and remains in the storage medium database. Preferably, the adjusted scores are stored only temporarily as candidates are evaluated for a particular position. Each candidate's adjusted skill scores are added together to yield a total that is used to compare the candidates. This information is provided to the employer who then selects a candidate for the position or job.
In spite of numerous candidate screening and testing techniques on the market that provide a general, descriptive assessment of a candidate, to date, there is no facile, accurate way to cross-reference between those screening and testing results, and the specific environment (i.e., the organization), where the candidate is intended for employment. Inter alia, this is due to the fact that human nature is too complex for a simple assessment analysis to achieve high levels of predictive ability in this area.
Research of pre-employment screening techniques shows that, in most cases, it is difficult to reach validity levels of 0.5 or more, through the utilization of combinations of all known techniques [see F. Schmidt, et al., “The Validity and Utility of Selection Methods in Personnel Psychology: Practical and Theoretical Implications of 85 Years of Research Findings”, Psychological Bulletin, 124, 262-274 (1998)]. Individual techniques of the prior art typically have validity levels of only 0.2-0.3.
There is therefore a recognized need for, and it would be highly advantageous to have, an assessment method for selecting a suitable candidate for a particular position in an organization that is straightforward, largely automatic, and attains extremely-high levels of predictive ability both in absolute terms and with respect to the predictive ability of assessment methods known in the art.